• Analytical Science and Technology
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• v.32 no.2
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• pp.56-64
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• 2019

Recently, a number of adulterated products, which are advertised as hair-growth enhancer have been emerged among those who suffer hair loss disease. For continuous control of illegal products, in this study, a rapid and sensitive method for simultaneous screening of 12 compounds that enhance hair-growth was established to protect public health by ultrahigh-performance liquid chromatography coupled to quadrupole-orbitrap mass spectrometry (UHPLC-Q-Orbitrap-MS). Fragmentation pathways of them were proposed based on $MS^2$ spectral data obtained using the established method. In this analysis, the LODs and LOQs ranged from 0.05 to 50 ng/mL and from 0.17 to 167 ng/mL, respectively. The square of the linear correlation coefficient ($R^2$) was determined as more than 0.995. The intra- and inter-assay accuracies were respective 88-112 % and 88-115 %. Their precision values were measured within 5 % (intra-day) and 10 % (inter-day). Mean recoveries of target compounds in adulterated products ranged from 84 to 115%. The relative standard deviation of stability was less than 12 % at $4^{\circ}C$ for 48 h. The method was employed to screen 14 dietary supplements advertised to be effective for the treatment of hair loss. Some of the products (~21 %) were proven to contain synthetic drugs that promote hair growth such as triaminodil, minoxidil, and finasteride.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.12
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• pp.62-69
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• 2020

The demand for industrial robots is proliferating with production automation. Industrial robots are used in various fields, such as logistics, welding, and assembly. Generally, six degrees of freedom are required to move freely in space. However, the palletizing robot used for material management and logistics systems typically has four degrees of freedom. In designing such robots, their main parts, such as motors and reducers, need to be adequately selected while satisfying payload requirements and speed. Hence, this study proposes a practical method for selecting the major parts based on dynamic analysis using ADAMS. First, the acceleration torques for the robot motion were found from the analysis, and then the friction torques were evaluated. This study introduces a constant-speed torque constant instead of friction coefficient. The RMS torque and maximum power of each motor were found considering the above torques. After that, this study recommends the major specifications of all motors and reducers. The proposed method was applied to a palletizing robot to verify the suitability of the pre-selected main parts. The verification result shows that the proposed method can be successfully applied to the early design stage of industrial robots.

• Steel and Composite Structures
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• v.38 no.1
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• pp.17-31
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• 2021

Post-earthquake fire is a common disaster which causes serious safety issues to infrastructures. This study aims to investigate the residual loading capacities of circular concrete-filled steel tube (CFST) columns under post-earthquake fire experimentally and numerically. The experimental programme contains two loading steps - pre-damage cyclic loading at room temperature and transient state tests with constant compression loads. Three finite element models are developed and validated against the test results. Upon validation, a total of 48 numerical results were generated in the parametric study to investigate the effects of thickness and strengths of steel tube, axial compression ratio and damage degree on the fire resistance of circular CFST columns. Based on the analysis on experimental and numerical results, the loading mechanism of circular CFST columns is discussed. A design method is proposed for the prediction of fire resistance time under different seismic pre-damage and compression loads. The predictions by the new method is compared with the newly generated experimental and numerical results and is found to be accurate and consistent with the mean value close to the unity and a coefficient of variation around 1%.

• Journal of radiological science and technology
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• v.45 no.2
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• pp.151-158
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• 2022

The Cardiac Gated Blood Pool (GBP) scintigram, a nuclear medicine imaging, calculates the left ventricular Ejection Fraction (EF) by segmenting the left ventricle from the heart. However, in order to accurately segment the substructure of the heart, specialized knowledge of cardiac anatomy is required, and depending on the expert's processing, there may be a problem in which the left ventricular EF is calculated differently. In this study, using the DeepLabV3 architecture, GBP images were trained on 93 training data with a ResNet-50 backbone. Afterwards, the trained model was applied to 23 separate test sets of GBP to evaluate the reproducibility of the region of interest and left ventricular EF. Pixel accuracy, dice coefficient, and IoU for the region of interest were 99.32±0.20, 94.65±1.45, 89.89±2.62(%) at the diastolic phase, and 99.26±0.34, 90.16±4.19, and 82.33±6.69(%) at the systolic phase, respectively. Left ventricular EF was calculated to be an average of 60.37±7.32% in the ROI set by humans and 58.68±7.22% in the ROI set by the deep learning segmentation model. (p<0.05) The automated segmentation method using deep learning presented in this study similarly predicts the average human-set ROI and left ventricular EF when a random GBP image is an input. If the automatic segmentation method is developed and applied to the functional examination method that needs to set ROI in the field of cardiac scintigram in nuclear medicine in the future, it is expected to greatly contribute to improving the efficiency and accuracy of processing and analysis by nuclear medicine specialists.

• Geomechanics and Engineering
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• v.31 no.5
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• pp.505-518
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• 2022

This study introduces soil resistance multipliers at locations encompassed by the zone of influence of the helix plate to consider the added lateral resistance provided to the helical pile. The zone of influence of a helix plate is a function of its diameter and serves as a boundary condition for the modified soil resistance springs. The concept is based on implementing p-multipliers as a reduction factor for piles in group action. The application of modified p-y springs in the analysis of helical piles allows for better characterization and understanding of the lateral behavior of helical piles, which will help further the development of design methods. To execute the proposed method, a finite difference program, HPCap (Helical Pile Capacity), was developed by the authors using Matlab. The program computes the deflection, shear force, bending moment, and soil resistance of the helical pile and allows the user to freely input the value of the zone of influence and Ω (a coefficient that affects the value of the p-multiplier). Results from ten full-scale lateral load tests on helical piles embedded at depths of 3.0 m with varying shaft diameters, shaft thicknesses, and helix configurations were analyzed to determine the zone of influence and the magnitude of the p-multipliers. The analysis determined that the value of the p-multipliers is influenced by the ratio between the pile embedment length and the shaft diameter (D_p), the effective helix diameter (D_h-D_p), and the zone of influence. Furthermore, the zone of influence is recommended to be 1.75 times the helix diameter (D_h). Using the numerical analysis method presented in this study, the predicted deflections of the various helical pile cases showed good agreement with the observed field test results.

• Advances in nano research
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• v.14 no.4
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• pp.375-389
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• 2023

In this study, free vibration analysis of functionally graded (FG) porous truncated conical shell panels reinforced by graphene platelets (GPLs) has been investigated for the first time. Additionally, the effect of three different types of porosity distribution and five different types of GPLs patterns on dynamic response of the shell are also studied. Halpin-Tsai micromechanical model and Voigt's rule are used to determine Young modulus, shear modulus and Poisson's ratio with mass densities of the shell, respectively. The main novelties of present study are: applying 3D elasticity theory and the finite element method in conjunction with Rayleigh-Ritz method to give more accurate results unlike other simplified shell theories, and also presenting a general 3D solution in cylindrical coordinate system that can be used for analyses of different structures such as circular, annular and annular sector plates, cylindrical shells and panels, and conical shells and panels. A convergence study is performed to justify the correctness of the obtained solution and numerical results. The impact of porosity and GPLs patterns, the volume of voids, the weight fraction of graphene nanofillers, semi vertex and span angles of the cone, and various boundary conditions on natural frequencies of the functionally graded panel have been comprehensively studied and discussed. The results show that the most important parameter on dynamic response of FG porous truncated conical panel is the weight fraction of nanofiller and adding 1% weight fraction of nanofiller could increase 57% approximately the amounts of natural frequencies of the shell. Moreover, the porosity distribution has great effect on the value of natural frequency of structure rather than the porosity coefficient.

• Current Optics and Photonics
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• v.7 no.4
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• pp.362-377
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• 2023

Optical information processing technology is characterized by high speed and parallelism, and the light features short wavelength and large information capacity; At the same time, it has various attributes including amplitude, phase, wavelength and polarization, and is a carrier of multi-dimensional information. Therefore, optical encryption is of great significance in the field of information security transmission, and is widely used in the field of image encryption. For multi-image encryption, this paper proposes a multi-image encryption algorithm based on a modified Gerchberg-Saxton algorithm (MGSA) in the Fresnel-transform domain and computational ghost imaging. First, MGSA is used to realize "one code, one key"; Second, phase function superposition and normalization are used to reduce the amount of ciphertext transmission; Finally, computational ghost imaging is used to improve the security of the whole encryption system. This method can encrypt multiple images simultaneously with high efficiency, simple calculation, safety and reliability, and less data transmission. The encryption effect of the method is evaluated by using correlation coefficient and structural similarity, and the effectiveness and security of the method are verified by simulation experiments.

• Analytical Science and Technology
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• v.21 no.1
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• pp.20-24
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• 2008

A chemiluminescence method has been developed to determine vitamin $P_1$ in aqueous solution which is based on the enhancement of the intensity of lucigenin using lucigenin-$H_2O_2$ as chemiluminogenic system. The effects of experimental parameters such as concentrations of lucigenin, pH and concentrations of $H_2O_2$ were studied. The present method allows the determination of vitamin $P_1$ over the range $7.5{\times}10^{-6}{\sim}5.0{\times}10^{-4}mol/L$. The detection limit was $5.7{\times}10^{-7}mol/L$. The relative standard deviation was 0.75 % for 10 determinations of $7.5{\times}10^{-5}mol/L$ vitamin $P_1$. The correlation coefficient of the working curve was 0.9984 (S/N=3).

• Structural Engineering and Mechanics
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• v.89 no.2
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• pp.181-197
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• 2024

A numerical method is presented in this paper, for buckling analysis of thin arbitrary stiffened composite cylindrical shells under axial compression. The stiffeners can be placed inside and outside of the shell. The shell and stiffeners are operated as discrete elements, and their interactions are taking place through the compatibility conditions along their intersecting lines. The governing equations of motion are obtained based on Koiter's theory and solved by utilizing the principle of the minimum potential energy. Then, the buckling load coefficient and the critical buckling load are computed by solving characteristic equations. In this formulation, the elastic and geometric stiffness matrices of a single curved strip of the shell and stiffeners can be located anywhere within the shell element and in any direction are provided. Moreover, five stiffened composite shell specimens are made and tested under axial compression loading. The reliability of the presented method is validated by comparing its numerical results with those of commercial software, experiments, and other published numerical results. In addition, by using the ANSYS code, a 3-D finite element model that takes the exact geometric arrangement and the properties of the stiffeners and the shell into consideration is built. Finally, the effects of Poisson's ratio, shell length-to-radius ratio, shell thickness, cross-sectional area, angle, eccentricity, torsional stiffness, numbers and geometric configuration of stiffeners on the buckling of stiffened composite shells with various end conditions are computed. The results gained can be used as a meaningful benchmark for researchers to validate their analytical and numerical methods.

• Steel and Composite Structures
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• v.51 no.4
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• pp.441-456
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• 2024

This paper aims to develop Machine Learning (ML) algorithms to predict the buckling resistance of cold-formed steel (CFS) channels with restrained flanges, widely used in typical CFS sheathed wall panels, and provide practical design tools for engineers. The effects of cross-sectional restraints were first evaluated on the elastic buckling behaviour of CFS channels subjected to pure axial compressive load or bending moment. Feedforward multi-layer Artificial Neural Networks (ANNs) were then trained on different datasets comprising CFS channels with various dimensions and properties, plate thicknesses, and restraining conditions on one or two flanges, while the elastic distortional buckling resistance of the elements were determined according to the Finite Strip Method (FSM). To develop less biased networks and ensure that every observation from the original dataset has the chance of appearing in the training and test set, a K-fold cross-validation technique was implemented. In addition, the hyperparameters of the ANNs were tuned using a grid search technique to provide ANNs with optimum performances. The results demonstrated that the trained ANNs were able to predict the elastic distortional buckling resistance of CFS flange-restrained elements with an average accuracy of 99% in terms of coefficient of determination. The developed models were then used to propose a simple ANN-based design formula for the prediction of the elastic distortional buckling stress of CFS flange-restrained elements. Finally, the proposed formula was further evaluated on a separate set of unseen data to ensure its accuracy for practical applications.